An Analytical Framework on Utilizing Various Integrated Multi-Trophic Scenarios for Basil Production

• Published in: Plants
• Main Authors: Petrea, Ștefan-Mihai, Simionov, Ira Adeline, Antache, Alina, Nica, Aurelia, Oprica, Lăcrămioara, Miron, Anca, Zamfir, Cristina Gabriela, Neculiță, Mihaela, Dima, Maricel Floricel, Cristea, Dragoș Sebastian
• Format: Text
• Language: English
• Published: MDPI 2023
• Subjects: Article; Gam; Acipenser baerii
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920146/; http://www.ncbi.nlm.nih.gov/pubmed/36771624; https://doi.org/10.3390/plants12030540

Here, we aim to improve the overall sustainability of aquaponic basil (Ocimum basilicum L.)-sturgeon (Acipenser baerii) integrated recirculating systems. We implement new AI methods for operational management together with innovative solutions for plant growth bed, consisting of Rapana venosa shells (R), considered wastes in the food processing industry. To this end, the ARIMA-supervised learning method was used to develop solutions for forecasting the growth of both fish and plant biomass, while multi-linear regression (MLR), generalized additive models (GAM), and XGBoost were used for developing black-box virtual sensors for water quality. The efficiency of the new R substrate was evaluated and compared to the consecrated light expended clay aggregate—LECA aquaponics substrate (H). Considering two different technological scenarios (A—high feed input, B—low feed input, respectively), nutrient reduction rates, plant biomass growth performance and additionally plant quality are analysed. The resulting prediction models reveal a good accuracy, with the best metrics for predicting N-NO(3) concentration in technological water. Furthermore, PCA analysis reveals a high correlation between water dissolved oxygen and pH. The use of innovative R growth substrate assured better basil growth performance. Indeed, this was in terms of both average fresh weight per basil plant, with 22.59% more at AR compared to AH, 16.45% more at BR compared to BH, respectively, as well as for average leaf area (LA) with 8.36% more at AR compared to AH, 9.49% more at BR compared to BH. However, the use of R substrate revealed a lower N-NH(4) and N-NO(3) reduction rate in technological water, compared to H-based variants (19.58% at AR and 18.95% at BR, compared to 20.75% at AH and 26.53% at BH for N-NH(4); 2.02% at AR and 4.1% at BR, compared to 3.16% at AH and 5.24% at BH for N-NO(3)). The concentration of Ca, K, Mg and NO(3) in the basil leaf area registered the following relationship between the experimental variants: AR > AH > BR ...